| Regularization with stochastic transformations and perturbations for deep semi-supervised learning M Sajjadi, M Javanmardi, T Tasdizen Advances in neural information processing systems 29, 2016 | 1147 | 2016 |
| Domain adaptation for biomedical image segmentation using adversarial training M Javanmardi, T Tasdizen 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 116 | 2018 |
| Mutual exclusivity loss for semi-supervised deep learning M Sajjadi, M Javanmardi, T Tasdizen 2016 IEEE International Conference on Image Processing (ICIP), 1908-1912, 2016 | 94 | 2016 |
| Using 164 million google street view images to derive built environment predictors of COVID-19 cases QC Nguyen, Y Huang, A Kumar, H Duan, JM Keralis, P Dwivedi, ... International journal of environmental research and public health 17 (17), 6359, 2020 | 83 | 2020 |
| Health and the built environment in United States cities: Measuring associations using Google Street View-derived indicators of the built environment JM Keralis, M Javanmardi, S Khanna, P Dwivedi, D Huang, T Tasdizen, ... BMC public health 20, 1-10, 2020 | 60 | 2020 |
| Google street view derived built environment indicators and associations with state-level obesity, physical activity, and chronic disease mortality in the United States L Phan, W Yu, JM Keralis, K Mukhija, P Dwivedi, KD Brunisholz, ... International Journal of Environmental Research and Public Health 17 (10), 3659, 2020 | 20 | 2020 |
| Leveraging 31 million Google street view images to characterize built environments and examine county health outcomes QC Nguyen, JM Keralis, P Dwivedi, AE Ng, M Javanmardi, S Khanna, ... Public Health Reports 136 (2), 201-211, 2021 | 19 | 2021 |
| Unsupervised total variation loss for semi-supervised deep learning of semantic segmentation M Javanmardi, M Sajjadi, T Liu, T Tasdizen arXiv preprint arXiv:1605.01368, 2016 | 18 | 2016 |
| SSHMT: Semi-supervised hierarchical merge tree for electron microscopy image segmentation T Liu, M Zhang, M Javanmardi, N Ramesh, T Tasdizen Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 15 | 2016 |
| Improving the robustness of convolutional networks to appearance variability in biomedical images T Tasdizen, M Sajjadi, M Javanmardi, N Ramesh 2018 IEEE 15th international symposium on biomedical imaging (ISBI 2018 …, 2018 | 14 | 2018 |
| Analyzing associations between chronic disease prevalence and neighborhood quality through Google Street View images M Javanmardi, D Huang, P Dwivedi, S Khanna, K Brunisholz, R Whitaker, ... IEEE Access 8, 6407-6416, 2019 | 11 | 2019 |
| Image segmentation by deep learning of disjunctive normal shape model shape representation M Javanmardi, R Bigolin Lanfredi, M Cetin, T Tasdizen Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 2 | 2018 |
| Appearance invariance in convolutional networks with neighborhood similarity T Tasdizen, M Sajjadi, M Javanmardi, N Ramesh arXiv preprint arXiv:1707.00755, 2017 | 2 | 2017 |
| Neighborhood Looking Glass: 360 Degree Automated Characterization of the Built Environment for Neighborhood Effects Research Q Nguyen, MM Sajjadi, M McCullough, W Yu, HW Meng, D Li, M Pham, ... I n APHA 2017 annual meeting & expo (nov. 4-Nov. 8). American Public Healt h …, 2017 | 1 | 2017 |
| Learning Deep Models Under Constraints of Annotated Data Insufficiency M Javanmardi The University of Utah, 2020 | | 2020 |
Tolga TasdizenUniversity of UtahVahvistettu sähköpostiosoite verkkotunnuksessa sci.utah.edu
